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        <a href="pln_inco.bioscope-module.html">Package&nbsp;bioscope</a> ::
        Module&nbsp;util
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<!-- ==================== MODULE DESCRIPTION ==================== -->
<h1 class="epydoc">Module util</h1><p class="nomargin-top"><span class="codelink"><a href="pln_inco.bioscope.util-pysrc.html">source&nbsp;code</a></span></p>
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        <a href="pln_inco.bioscope.util.BioscopeCorpusProcessor-class.html" class="summary-name">BioscopeCorpusProcessor</a><br />
      M&#233;todos para procesar el corpus original, generando eventualmente 
        archivos intermedios
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      <span class="summary-type"><code>String</code></span>
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          <td><span class="summary-sig"><a href="pln_inco.bioscope.util-module.html#bioscope_get_text" class="summary-sig-name">bioscope_get_text</a>(<span class="summary-sig-arg">xml_element</span>)</span><br />
      Funci&#243;n auxiliar que obtiene el texto abarcado por un elemento xml 
      del corpus bioscope sin las marcas intermedias</td>
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            <span class="codelink"><a href="pln_inco.bioscope.util-pysrc.html#bioscope_get_text">source&nbsp;code</a></span>
            
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          <td><span class="summary-sig"><a href="pln_inco.bioscope.util-module.html#bioscope_retokenize" class="summary-sig-name">bioscope_retokenize</a>(<span class="summary-sig-arg">genia_words</span>,
        <span class="summary-sig-arg">bioscope_tokens</span>)</span><br />
      Dada una lista de palabras resultado de la tokenizaci&#243;n por el tagger
      de genia y otra lista resultado de la tokenizaci&#243;n del texto 
      utilizando <code>nltk.tokenize.TreebankWordTokenizer()</code>, 
      retokeniza al segundo para que quede igual al de Genia.</td>
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  <h3 class="epydoc"><span class="sig"><span class="sig-name">bioscope_get_text</span>(<span class="sig-arg">xml_element</span>)</span>
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    ><span class="codelink"><a href="pln_inco.bioscope.util-pysrc.html#bioscope_get_text">source&nbsp;code</a></span>&nbsp;
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  <p>Funci&#243;n auxiliar que obtiene el texto abarcado por un elemento xml del
  corpus bioscope sin las marcas intermedias</p>
  <dl class="fields">
    <dt>Parameters:</dt>
    <dd><ul class="nomargin-top">
        <li><strong class="pname"><code>xml_element</code></strong> (<code>xml.etree.ElementTree</code>) - XML del corpus Bioscope</li>
    </ul></dd>
    <dt>Returns: <code>String</code></dt>
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  <h3 class="epydoc"><span class="sig"><span class="sig-name">bioscope_retokenize</span>(<span class="sig-arg">genia_words</span>,
        <span class="sig-arg">bioscope_tokens</span>)</span>
  </h3>
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    ><span class="codelink"><a href="pln_inco.bioscope.util-pysrc.html#bioscope_retokenize">source&nbsp;code</a></span>&nbsp;
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  <p>Dada una lista de palabras resultado de la tokenizaci&#243;n por el tagger 
  de genia y otra lista resultado de la tokenizaci&#243;n del texto utilizando 
  <code>nltk.tokenize.TreebankWordTokenizer()</code>, retokeniza al segundo
  para que quede igual al de Genia.</p>
  <dl class="fields">
    <dt>Parameters:</dt>
    <dd><ul class="nomargin-top">
        <li><strong class="pname"><code>genia_words</code></strong> (<code>List</code>) - lista de palabras, resultado del an&#225;lisis con el Genia Tagger</li>
        <li><strong class="pname"><code>bioscope_tokens</code></strong> (<code>List</code>) - lista de tokens resultado del an&#225;lisis con 
          <code>nltk.tokenize.TreebankWordTokenizer()</code></li>
    </ul></dd>
    <dt>Returns: <code>List</code></dt>
        <dd>bioscope_tokens, retokenizado</dd>
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